About Data

Telcom Customer Churn - Context: “Predict behavior to retain customers. You can analyze all relevant customer data and develop focused customer retention programs.” [IBM Sample Data Sets]

Content: The raw data contains 7043 rows (customers) and 21 columns (features).

Rows: 7,043
Columns: 21
$ customer_id       <chr> "7590-VHVEG", "5575-GNVDE", "3668-QPYBK", "7795-CFOC…
$ gender            <chr> "Female", "Male", "Male", "Male", "Female", "Female"…
$ senior_citizen    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ partner           <chr> "Yes", "No", "No", "No", "No", "No", "No", "No", "Ye…
$ dependents        <chr> "No", "No", "No", "No", "No", "No", "Yes", "No", "No…
$ tenure            <dbl> 1, 34, 2, 45, 2, 8, 22, 10, 28, 62, 13, 16, 58, 49, …
$ phone_service     <chr> "No", "Yes", "Yes", "No", "Yes", "Yes", "Yes", "No",…
$ multiple_lines    <chr> "No phone service", "No", "No", "No phone service", …
$ internet_service  <chr> "DSL", "DSL", "DSL", "DSL", "Fiber optic", "Fiber op…
$ online_security   <chr> "No", "Yes", "Yes", "Yes", "No", "No", "No", "Yes", …
$ online_backup     <chr> "Yes", "No", "Yes", "No", "No", "No", "Yes", "No", "…
$ device_protection <chr> "No", "Yes", "No", "Yes", "No", "Yes", "No", "No", "…
$ tech_support      <chr> "No", "No", "No", "Yes", "No", "No", "No", "No", "Ye…
$ streaming_tv      <chr> "No", "No", "No", "No", "No", "Yes", "Yes", "No", "Y…
$ streaming_movies  <chr> "No", "No", "No", "No", "No", "Yes", "No", "No", "Ye…
$ contract          <chr> "Month-to-month", "One year", "Month-to-month", "One…
$ paperless_billing <chr> "Yes", "No", "Yes", "No", "Yes", "Yes", "Yes", "No",…
$ payment_method    <chr> "Electronic check", "Mailed check", "Mailed check", …
$ monthly_charges   <dbl> 29.85, 56.95, 53.85, 42.30, 70.70, 99.65, 89.10, 29.…
$ total_charges     <dbl> 29.85, 1889.50, 108.15, 1840.75, 151.65, 820.50, 194…
$ churn             <chr> "No", "No", "Yes", "No", "Yes", "Yes", "No", "No", "…

BI Analysis

Linha 1

Total Churn

1869

Total Customers

7043

% Churn Rate

26.54

linha dois

Monthly % Churn Rate

linha tres

Exploratory Analysis (EDA)

Esta análise envolve a exploração dos dados brutos em busca de relações, padrões e tendências. Ela ajuda a identificar variáveis importantes e pode fornecer insights para análises mais avançadas.

Linha 1

Plot Vars Types

Plot Missing Values

Statistical Analysis

Linha 1

Plot Density

Plot Histogram

Machine Learning

Classifying Personas through clusters